Statistics is best learnt by doing. The homework problems are
intended to help you understand the methods we discuss in class, and
apply them to solve problems. I also try to set homework problems
that make interesting points.

There will be four homework sets, one for each of the major
sections of the course. They will be distributed in the middle of the
appropriate set of lectures and due approximately one or two weeks after
lectures on that topic.
Each homework set will consist of four problems. Most problems will have
have multiple parts. You are to turn in
answers to three of the four problems. The first two problems are
intended to be simpler than the last two, so I presume most of you
will answer the first two problems and choose one of the second two.
However, the choice is yours. In general, the four problems will be:

An ecological question (or questions), a set of data, and a serious
of specific things to do.

Some theoretical question(s) about the methods.

An ecological question and data set. You are to decide what should
be done to answer the question.

More complicated theoretical question(s) about the methods.

You are encouraged to work together on the problems. I encourage
groups to include both statisticians and non-statisticians. However, you
must each write your own answers. Copying will not be tolerated.

Some of the problems during the semester will be labelled "Major data questions".
Your answer to these problems should be in the following form:

'Executive summary' or abstract: short statement of question,
approach, and answer. Should be no more than one paragraph. No formulae
or technical language here. This should be written for the busy
plant manager or state regulator.

Approach: Describe your model or approach. Briefly explain why
you chose it. Describe computational approach. If you considered
multiple models, do not explain all
of them in detail. Just say what you considered and the reasons for
your final choice.

Answer: answer the environmental question(s) using the 'final' model.
Make sure you provide
the context for the answer. For example, saying 'Estimated Phi
equals 0.2349887' is not a sufficient answer because it does not
provide context (what is Phi? How precise is the estimate? How big a
value really matters?). You must interpret the answer. Estimates of
precision (or confidence intervals) are (almost) always useful.

Critique: use model diagnostics (if appropriate and available)
or other information to critique your answer. What, if any, are the
weaknesses or problematic assumptions? Another way to critique your
answer is to discuss what are better models/methods to use if you
had more time. You should discuss (briefly) why each model or
method would be more appropriate. I
do not want a laundry list of all possible analyses.

I expect total length to be no more than three pages for each data
problem.

Answers to the "short" data questions and theoretical questions
are more straightforward.
Answer the question, showing your work.

Please ask me if you have any questions about the problems. I am
very willing to give advice, especially about computing.

I give
you two to three weeks to work on the assignment because I don't think the
problems can be answered overnight. Please do not wait until the
day before to start working.